This project, part of the "Go Blue project," used AI, specifically machine learning, for remote sensing to extract land cover information from satellite imagery to prepare an integrated strategic urban development plan for Hola Town, Kenya. It used open-source datasets from AI processes to fill data gaps.
Activity Type Research/Reports/AssessmentsTechnical assistance
UNITAC developed BEAM, a model that uses machine learning to accelerate the spatial recognition of informal settlements and building structures on aerial imagery. The tool provides up-to-date geo-referenced base maps and includes a technology and knowledge transfer component to build capacity.
Mapping a community inherently makes it “legible” to public authorities. Doing so can have tremendous advantages for the planning and allocation of critical public health and infrastructure services, especially in slum settlements. However, such data collection must respect both the privacy of residents and their unique cultural dynamics.
A comprehensive guide designed to help cities and communities leverage digital technologies for sustainable development. The toolkit, developed with 13 UN entities, provides practical strategies and tools through 12 modules covering topics from governance to smart manufacturing.
Activity Type Research/Reports/AssessmentsPolicy/Regulatory GuidanceAwareness/AdvocacyUNITAC is developing a toolkit on the use of artificial intelligence (AI) for spatial mapping and analysis for urban planners and policy makers, providing support on how they can adopt AI solutions to address urban challenges.
Activity Type AI Tools/SolutionsResearch/Reports/AssessmentsAwareness/Advocacy